I've now done some further research and read the comments.

By far, my conclusion is that, SSL is indeed, a type of SL. It contains features and corresponding label(s). From wikipedia:

>Supervised learning (SL) is a machine learning paradigm for problems where the available data consists of labeled examples, meaning that each data point contains features (covariates) and an associated label.

Since this is not a debate, I do not want to dwell on the definition. And indeed, *self-*supervised means that it does not require extra resource-consuming labelling from human, making training with huge datasets possible, like GPT-3.

And I disagree that seeing SSL as a kind of SL is the "wrong level" as a comment suggestted. What I originally intended to confirm was that, language modeling, which gives rise to GPT-3/ChatGPT... Is a kind of supervised learning with a large quantity (and sometimes good quality) of data. Strong model with simple, old methods.